对江苏省部分中小学体育教学中学习评价的研究

体育教学评价是体育教学改革的一个焦点问题，而学生的学习评价又是教学评价中的重点，随着体育教学改革的不断深入，原有的从学生运动技术和身体素质为主要评价内容的评价体系已不能体现“健康第一”的指导思想，所以，需要对体育教学评价体系进行改革。通过对江苏省部分中、小学体育教师和学生的访谈，对体育教学评价体系中学习评价的改革提出建设性意见。     

推送系统的模糊神经网络控制

将模糊逻辑推理方法与神经网络技术相结合组成的模糊神经网络控制器,可利用神经网络的高效和并行学习机理对模糊逻辑系统进行学习和修正,大大改善了系统的学习性能,仿真结果表明这种控制器不仅算法简单,控制实时性也高。     

Nostalgic research reflections

This research aimed to generate opportunities for UK construction companies, particularly contractors and consultancies with 50 to 150 employees to improve relationships with clients and to increase effectiveness through the exploitation of communication procedures and technologies. The research team used an action learning approach to work with managers from construction companies and housing associations to design and deliver support mechanisms, such as industry workshops, specific to the needs of SMEs. Analysis of the results showed how, as a result of interacting with other groups within a non-adversarial environment and benefiting from the process, partnering and performance improvement came to be seen as both desirable and possible. The trust and confidence generated from working together successfully also led construction SMEs to share good practice with others from the industry, including local competitors. The authors propose that SMEs should be treated as ‘leaders’ and ‘full partners’ within the programme for UK industry improvement being championed by Sir John Egan (1998), rather than simply recipients. It is also suggested that governments provide further support to ensure participation from small and micro firms.

Cette étude a pour objectif de geénérer des opportunités pour les entreprises britanniques du bâtiment, notamment pour les entrepreneurs et les bureaux d'ingénieurs conseil employant de 50 à 150 personnes, afin d'améliorer les relations avec la clientè le et accroîitre l'efficacité grâce à l'exploitation des procédures et des technologies de communication. Lors de ses travaux avec les responsables de la construction et de l'habitat, l'équipe de recherche a adopté une approche basée sur l'apprentissage des processus afin de concevoir et de fournir des mécanismes de support, tels que des ateliers industriels, spécifiques aux besoins des PME. L'analyse des résultats a révelé la f?on dont, suite à l'interaction avec d'autres groupes au sein d'un environnement non concurrentiel et tirant avantage du processes, l'amélioration du partenariat et des performances pouvait s'avérer à la fois souhaitable et possible. La confiance générée par la réussite de la collaboration a également conduit les PME du bâtiment à partager leurs bonnes pratiques avec d'autres acteurs de l'industrie, concurrents locaux inclus. Les auteurs proposent de traiter les PME en tant que ‘leaders’ et ‘partenaires à part entière’ dans le cadre du programme pour l'amélioration de l'industrie britannique défendu par Sir John Egan (1998), et non comme de simples récipiendaires. Il est également suggéré que les gouvernements fournissent d'autres subventions pour garantir la participation des petites et des micro-entreprises.     

What is IAQ?

In spaces for human occupancy indoor air quality (IAQ) is often defined as the extent to which human requirements are met. But what requirements do people have in relation to indoor air? The desire is that the air be perceived as fresh and pleasant, that it has no negative impact on their health, and that the air is stimulating and promotes their work, i.e. it increases their productivity and the learning of their children in the classroom at school. Present ventilation standards and guidelines do not care about productivity and learning and have the very modest requirement that the indoor air shall be 'acceptable,' meaning that the most sensitive group of persons (usually 20%) perceive the air as unacceptable while the remaining less sensitive persons may find the air barely acceptable. With such a modest aim it is not surprising that comprehensive field studies in many countries in buildings in which ventilation standards are met show high percentages of dissatisfied persons and of those suffering from sick building syndrome symptoms. Recent studies show that improvement of IAQ by a factor of 2-7 compared with existing standards increases office productivity and school learning significantly, while decreasing the risk of allergic symptoms and asthma in homes. To make indoor air acceptable, even for the most sensitive persons, an improvement of 1-2 orders of magnitude may be required. The paper will discuss the development of new methods that can provide such substantial improvements of IAQ while maintaining or even decreasing ventilation and energy usage. A paradigm shift is required and further future shifts are foreseen where we learn how to make indoor air equally fresh and pleasant as outdoors when it is best. Or even better, i.e. 'out of this world.' PRACTICAL IMPLICATIONS: The paper estimates an enormous potential for improving IAQ in practice utilizing new emerging technologies. This will enable us to provide IAQ which is acceptable even for the most sensitive persons. Already modest improvements compared to present minimum standards and typical conditions in practice can significantly decrease the risk of asthma/allergy in homes, improve learning in schools and increase productivity.     

End-to-End Multiview Gesture Recognition for Autonomous Car Parking System

The use of hand gestures can be the most intuitive human-machine interaction medium.The early approaches for hand gesture recognition used device-based methods....     

基于相似度聚类分析的动态背景建模与减除

对复杂动态背景建模技术进行了研究,提出了一种基于像素相似度聚类分析的动态背景建模算法.该算法首先建立融合亮度和色度信息的像素相似度理论,然后用像素相似评价标准对图像各像素点像素值的时间序列进行聚类分析,以建立动态背景模型.最后,利用该背景模型进行了多场景前景检测对比实验和算法内存消耗以及算法单帧处理时间等性能测试.实验结果表明,该算法前景检测准确度高,时间和空间上的复杂度低.     

Blended Learning – ein innovatives Weiterbildungskonzept für die Technische Chemie

The ever‐increasing and ever‐changing challenges of the job market require professionals to constantly attend extra occupational education programs. Professionals furthermore express their desire for a compatibility of family and work. Therefore, a general concept for extended vocational training in the field of natural science and technology was developed based on blended learning. As an example, the concept was implemented and tested on the basis of the extended vocational training course “tc‐compact^BL” in Chemical Technology.     

Models for solar radiation prediction based on different measurement sites

The modeling of solar radiation for forecasting its availability is a key tool for managing photovoltaic (PV) plants and, hence, is of primary importance for energy production in a smart grid scenario. However, the variability of the weather phenomena is an unavoidable obstacle in the prediction of the energy produced by the solar radiation conversion. The use of the data collected in the past can be useful to capture the daily and seasonal variability, while measurement of the recent past can be exploited to provide a short term prediction. It is well known that a good measurement of the solar radiation requires not only a high class radiometer, but also a correct management of the instrument. In order to reduce the cost related to the management of the monitoring apparatus, a solution could be to evaluate the PV plant performance using data collected by public weather station installed near the plant. In this paper, two experiments are conducted. In the first, the plausibility of the short term prediction of the solar radiation, based on data collected in the near past on the same site is investigated. In the second experiment, the same prediction is operated using data collected by a public weather station located at ten kilometers from the solar plant. Several prediction techniques belonging from both computational intelligence and statistical fields have been challenged in this task. In particular, Support Vector Machine for Regression, Extreme Learning Machine and Autoregressive models have been used and compared with the persistence and the k-NN predictors. The prediction accuracy achieved in the two experimental conditions are then compared and the results are discussed.     

不确定性X-Y定位平台PID控制方法研究

X-Y定位平台属于强耦合非线性系统,且由于结构复杂性及外界干扰,当前测量水平难以获得其精确的数学模型,提出基于自适应神经网络的PID控制策略。考虑到X-Y定位平台系统精确的数学模型难以获得,利用神经网络良好的学习能力来逼近系统未知非线性模型,设计神经网络控制器;为了保证神经网络在学习的初期阶段的控制精度,设计PID控制器来进行辅助补偿控制;为加快学习速度,提高运动控制的实时性,设计变学习率的优化算法来实现神经网络权值的在线调整。试验结果验证了所提控制方法的有效性。     

深度残差网络在滚动轴承故障诊断中的研究

近年来,由于传统人工提取特征的方法不足以准确表征滚动轴承的健康状态,深度学习算法被逐渐应用于滚动轴承的故障诊断中,它能够自适应的从输入数据中学习出所需要的特征.其中,相较于普通的深度学习算法,深度残差网络通过恒等映射的方式可以大幅度降低模型的训练难度.因此,采用了一种用于滚动轴承故障诊断的深度残差网络(ResNet),...